摘要
本文在总结自组织映射(Self-OrganizingMap,SOM)神经网络的工作原理及实现过程的基础上,分析了内燃机的典型性能指标与故障类型之间的关系,并以某型号内燃机的振动信号为样本,利用经迭代训练后的网络结构对其进行检测,以此判断设备的工作状态。基于SOM神经网络的内燃机故障诊断模型,具有较好的诊断效果。
Based on the summary of the working principle and implementation process of Self-Organizing Map(SOM) neural network, this paper analyzes the relationship between typical performance indexes and fault types of internal combustion engines, and uses the vibration signal of a model of internal combustion engine as a sample to detect it using the network structure after iterative training, so as to determine the working status of the equipment. The fault diagnosis model of internal combustion engine based on SOM neural network has a good diagnosis effect.
作者
李林
吴玲
LI Lin;WU Ling(Shaanxi Institute of Technology,Xi’an Shannxi 710300,China)
出处
《信息与电脑》
2022年第19期67-69,共3页
Information & Computer
基金
2020年度陕西国防工业职业技术学院研究项目“基于航空结构件制造柔性工装系统开发”(项目编号:Gfy20-17)。
关键词
自组织映射(SOM)神经网络
内燃机故障
故障诊断
Self-Organizing Map(SOM)neural network
internal combustion engine fault
fault diagnosis